One of conventional image recognizing apparatus is known as disclosed in the Japanese Patent of (Publication No. 9-21610).
FIG. 35 is a block diagram of a conventional image recognizing apparatus which comprises:
(a) image input unit 3511 for receiving an image of interest;
(b) model memory unit 3512 which stores local models of an object to be identified;
(c) matching process unit 3513 for matching each image segment of the input image with the local models;
(d) local data integrating unit 3514 for integrating and displaying, in probabilistic way, the position of the object to be identified in a parameter space together with the position of the image segment depending on the degree of the matching of each image segment of the input image with its local model; and
(e) object position determining unit 3515 for determining image segments with the highest probability from the parameter space to determine the position of the object to be identified in the input image.
The conventional image recognizing apparatus may carry out the recognizing operation with much difficulty as a number of similar local models of different models are increased.
Another conventional image recognizing apparatus is also known as disclosed in the Japanese Patent (Publication No. 6-215140).
FIG. 36 is a block diagram of the another conventional image recognizing apparatus which comprises:
(a) display 3601 for displaying an image;
(b) main controller 3602 for controlling operations of the entire system;
(c) internal memory 3603 for storing an operating program and the like;
(d) disk 3604 for storing a reference pattern;
(e) television camera 3605 for capturing an image of an object to be identified such as a product or a sample;
(f) image input unit 3606 for converting image data of the object captured by camera 3605 into a digital form;
(g) image rotating unit 3607 for positioning the object in a gradation image of the digital form to be faced in a given direction for each category;
(h) image data extracting unit 3608 for sampling the rotated image at a specific rate and extracting the gradation of each sampled image as characteristic data of the rotated image;
(i) dictionary generating unit 3609, having average vector calculator 3609A for calculating an average vector of the images of each category from the characteristic data, for determining a dictionary (a list of reference patterns) of the average vectors;
(j) identifying unit 3610 having vector distance comparator 3610A for calculating a vector of an object of an unknown category and for extracting, from the dictionary generating unit 3609, one of the average vectors which is closest to the calculated vector to identify the object on the unknown category; and
(j) parameter setting unit 3611 for optimizing the parameters for image input 3606, the image rotating unit 3607, image data extracting unit 3608, and identifying unit 3610 in each category.
The another conventional image recognizing apparatus may hardly carry out the recognizing operation in case that the images of objects which are identical in the shape but different in the gradation are grouped in one category for recognizing and classifying the objects by shape. Since similar gradation images are grouped into one category, a total number of categories increases thus requiring more time for the operation.